Lines are an integral aspect of representing things (e.g., lane markers, poles, curbs, edges of buildings, etc.) in an electronic form. In general, a computing system may represent a line using, for example, six or more values as a parameterization. The values may correspond with endpoints of the line, directional vectors for the line, lengths, and so on. In either case, the use of a number of values beyond the corresponding degrees of freedom for a line results in the line feature being overparameterized.
Consequently, the overparameterized line feature can introduce difficulties into how the representation is applied in different applications. For example, initial observations of the line feature can include noise within sensor data that is from various sources. The presence of noise and thus the extrapolation of an uncertainty for detection of the line feature can complicate further determinations due to the overparameterization.
For example, aspects such as determining corresponding features between observed features and mapped features in a predefined map may result in duplicated features and/or in difficulties determining uncertainties of correlations. Such issues result from, in one aspect, difficulties in representing the observed uncertainty using a probabilistic approach. Therefore, representing line features using an overparameterization of values can result in difficulties when applying the observed line features in different frameworks.